Merge pull request #845 from roboflow/feature/adding_notifiers_blocks

Add Slack and Twilio notifiers

docker/dockerfiles/Dockerfile.onnx.lambda

@@ -74,6 +74,7 @@ ENV ALLOW_CUSTOM_PYTHON_EXECUTION_IN_WORKFLOWS=False
 ENV CORE_MODEL_TROCR_ENABLED=false
 ENV USE_FILE_CACHE_FOR_WORKFLOWS_DEFINITIONS=False
 ENV ALLOW_WORKFLOW_BLOCKS_ACCESSING_LOCAL_STORAGE=False
+ENV ALLOW_WORKFLOW_BLOCKS_ACCESSING_ENVIRONMENTAL_VARIABLES=False
 
 WORKDIR ${LAMBDA_TASK_ROOT}
 RUN rm -rf /build

docker/dockerfiles/Dockerfile.onnx.lambda.slim

@@ -69,6 +69,7 @@ ENV CORE_MODEL_TROCR_ENABLED=false
 ENV ENABLE_WORKFLOWS_PROFILING=True
 ENV USE_FILE_CACHE_FOR_WORKFLOWS_DEFINITIONS=False
 ENV ALLOW_WORKFLOW_BLOCKS_ACCESSING_LOCAL_STORAGE=False
+ENV ALLOW_WORKFLOW_BLOCKS_ACCESSING_ENVIRONMENTAL_VARIABLES=False
 
 WORKDIR ${LAMBDA_TASK_ROOT}
 

docs/workflows/blocks.md

@@ -79,6 +79,7 @@ hide:
 <p class="card block-card" data-url="qr_code_detection" data-name="QR Code Detection" data-desc="Detect and read QR codes in an image." data-labels="MODEL, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="single_label_classification_model" data-name="Single-Label Classification Model" data-desc="Apply a single tag to an image." data-labels="MODEL, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="roboflow_custom_metadata" data-name="Roboflow Custom Metadata" data-desc="Add custom metadata to Roboflow Model Monitoring dashboard" data-labels="SINK, APACHE-2.0" data-author="dummy"></p>
+<p class="card block-card" data-url="model_monitoring_inference_aggregator" data-name="Model Monitoring Inference Aggregator" data-desc="Periodically report an aggregated sample of inference results to Roboflow Model Monitoring" data-labels="SINK, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="instance_segmentation_model" data-name="Instance Segmentation Model" data-desc="Predict the shape, size, and location of objects." data-labels="MODEL, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="keypoint_detection_model" data-name="Keypoint Detection Model" data-desc="Predict skeletons on objects." data-labels="MODEL, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="multi_label_classification_model" data-name="Multi-Label Classification Model" data-desc="Apply multiple tags to an image." data-labels="MODEL, APACHE-2.0" data-author="dummy"></p>
@@ -104,6 +105,9 @@ hide:
 <p class="card block-card" data-url="trace_visualization" data-name="Trace Visualization" data-desc="Draws traces based on detections tracking results." data-labels="VISUALIZATION, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="reference_path_visualization" data-name="Reference Path Visualization" data-desc="Draws a reference path in the image" data-labels="VISUALIZATION, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="webhook_sink" data-name="Webhook Sink" data-desc="Sends the request to remote API with results of Workflow results" data-labels="SINK, APACHE-2.0" data-author="dummy"></p>
+<p class="card block-card" data-url="environment_secrets_store" data-name="Environment Secrets Store" data-desc="Fetches secrets from environmental variables" data-labels="SECRETS_PROVIDER, APACHE-2.0" data-author="dummy"></p>
+<p class="card block-card" data-url="slack_notification" data-name="Slack Notification" data-desc="Send notification via Slack" data-labels="SINK, APACHE-2.0" data-author="dummy"></p>
+<p class="card block-card" data-url="twilio_sms_notification" data-name="Twilio SMS Notification" data-desc="Send notification via Twilio SMS service" data-labels="SINK, APACHE-2.0" data-author="dummy"></p>
 <!--- AUTOGENERATED_BLOCKS_LIST -->
     </div>
   </div>

docs/workflows/execution_engine_changelog.md

@@ -301,3 +301,20 @@ subsets of steps**, enabling building such tools as debuggers.
         feel free to alter the serialization methods for *kinds*, simply registering
         the function in your plugin and loading it to the Execution Engine - the 
         serializer/deserializer defined as the last one will be in use.
+
+
+## Execution Engine `v1.4.0` | inference `v0.29.0`
+
+* Added new kind - [`secret`](/workflows/kinds/secret/) to represent credentials. **No action needed** for existing 
+blocks, yet it is expected that over time blocks developers should use this kind, whenever block is to accept secret 
+value as parameter.
+
+* Fixed issue with results serialization introduced in `v1.3.0` - by mistake, Execution Engine was not serializing 
+non-batch oriented outputs.
+
+* Fixed Execution Engine bug with preparing inputs for steps. For non-SIMD steps before, while collecting inputs 
+in runtime, `WorkflowBlockManifest.accepts_empty_input()` method result was being ignored - causing the bug when
+one non-SIMD step was feeding empty values to downstream blocks. Additionally, in the light of changes made in `v1.3.0`,
+thanks to which non-SIMD blocks can easily feed inputs for downstream SIMD steps - it is needed to check if 
+upstream non-SIMD block yielded non-empty results (as SIMD block may not accept empty results). This check was added.
+**No action needed** for existing blocks, but this fix may fix previously broken Workflows.

docs/workflows/gallery_index.md

@@ -8,13 +8,15 @@ Browse through the various categories to find inspiration and ideas for building
 	<li><a href="/workflows/gallery/workflows_enhanced_by_roboflow_platform">Workflows enhanced by Roboflow Platform</a></li>
 	<li><a href="/workflows/gallery/basic_workflows">Basic Workflows</a></li>
 	<li><a href="/workflows/gallery/workflows_with_classical_computer_vision_methods">Workflows with classical Computer Vision methods</a></li>
+	<li><a href="/workflows/gallery/workflows_with_visualization_blocks">Workflows with visualization blocks</a></li>
 	<li><a href="/workflows/gallery/workflows_with_visual_language_models">Workflows with Visual Language Models</a></li>
+	<li><a href="/workflows/gallery/data_analytics_in_workflows">Data analytics in Workflows</a></li>
 	<li><a href="/workflows/gallery/workflows_with_dynamic_python_blocks">Workflows with dynamic Python Blocks</a></li>
 	<li><a href="/workflows/gallery/workflows_for_ocr">Workflows for OCR</a></li>
 	<li><a href="/workflows/gallery/workflows_with_data_transformations">Workflows with data transformations</a></li>
 	<li><a href="/workflows/gallery/workflows_with_flow_control">Workflows with flow control</a></li>
 	<li><a href="/workflows/gallery/workflows_with_business_logic">Workflows with business logic</a></li>
 	<li><a href="/workflows/gallery/advanced_inference_techniques">Advanced inference techniques</a></li>
 	<li><a href="/workflows/gallery/workflows_with_foundation_models">Workflows with foundation models</a></li>
-	<li><a href="/workflows/gallery/workflows_with_visualization_blocks">Workflows with visualization blocks</a></li>
+	<li><a href="/workflows/gallery/integration_with_external_apps">Integration with external apps</a></li>
 </ul>

docs/workflows/kinds.md

@@ -68,38 +68,39 @@ providing compile-time verification of Workflows definitions.
 
 ## Kinds declared in Roboflow plugins
 <!--- AUTOGENERATED_KINDS_LIST -->
-* [`object_detection_prediction`](/workflows/kinds/object_detection_prediction): Prediction with detected bounding boxes in form of sv.Detections(...) object
+* [`float_zero_to_one`](/workflows/kinds/float_zero_to_one): `float` value in range `[0.0, 1.0]`
+* [`image_keypoints`](/workflows/kinds/image_keypoints): Image keypoints detected by classical Computer Vision method
 * [`float`](/workflows/kinds/float): Float value
 * [`image_metadata`](/workflows/kinds/image_metadata): Dictionary with image metadata required by supervision
-* [`prediction_type`](/workflows/kinds/prediction_type): String value with type of prediction
-* [`*`](/workflows/kinds/*): Equivalent of any element
-* [`dictionary`](/workflows/kinds/dictionary): Dictionary
-* [`roboflow_api_key`](/workflows/kinds/roboflow_api_key): Roboflow API key
-* [`classification_prediction`](/workflows/kinds/classification_prediction): Predictions from classifier
-* [`video_metadata`](/workflows/kinds/video_metadata): Video image metadata
-* [`detection`](/workflows/kinds/detection): Single element of detections-based prediction (like `object_detection_prediction`)
-* [`boolean`](/workflows/kinds/boolean): Boolean flag
+* [`object_detection_prediction`](/workflows/kinds/object_detection_prediction): Prediction with detected bounding boxes in form of sv.Detections(...) object
+* [`integer`](/workflows/kinds/integer): Integer value
 * [`bytes`](/workflows/kinds/bytes): This kind represent bytes
-* [`qr_code_detection`](/workflows/kinds/qr_code_detection): Prediction with QR code detection
-* [`contours`](/workflows/kinds/contours): List of numpy arrays where each array represents contour points
-* [`language_model_output`](/workflows/kinds/language_model_output): LLM / VLM output
-* [`inference_id`](/workflows/kinds/inference_id): Inference identifier
-* [`serialised_payloads`](/workflows/kinds/serialised_payloads): Serialised element that is usually accepted by sink
-* [`string`](/workflows/kinds/string): String value
-* [`float_zero_to_one`](/workflows/kinds/float_zero_to_one): `float` value in range `[0.0, 1.0]`
-* [`rgb_color`](/workflows/kinds/rgb_color): RGB color
-* [`image`](/workflows/kinds/image): Image in workflows
-* [`roboflow_project`](/workflows/kinds/roboflow_project): Roboflow project name
-* [`top_class`](/workflows/kinds/top_class): String value representing top class predicted by classification model
-* [`image_keypoints`](/workflows/kinds/image_keypoints): Image keypoints detected by classical Computer Vision method
+* [`roboflow_model_id`](/workflows/kinds/roboflow_model_id): Roboflow model id
+* [`boolean`](/workflows/kinds/boolean): Boolean flag
 * [`list_of_values`](/workflows/kinds/list_of_values): List of values of any type
 * [`instance_segmentation_prediction`](/workflows/kinds/instance_segmentation_prediction): Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object
-* [`keypoint_detection_prediction`](/workflows/kinds/keypoint_detection_prediction): Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object
-* [`numpy_array`](/workflows/kinds/numpy_array): Numpy array
+* [`video_metadata`](/workflows/kinds/video_metadata): Video image metadata
+* [`secret`](/workflows/kinds/secret): Secret value
+* [`classification_prediction`](/workflows/kinds/classification_prediction): Predictions from classifier
+* [`string`](/workflows/kinds/string): String value
 * [`bar_code_detection`](/workflows/kinds/bar_code_detection): Prediction with barcode detection
-* [`roboflow_model_id`](/workflows/kinds/roboflow_model_id): Roboflow model id
-* [`integer`](/workflows/kinds/integer): Integer value
-* [`parent_id`](/workflows/kinds/parent_id): Identifier of parent for step output
 * [`point`](/workflows/kinds/point): Single point in 2D
+* [`parent_id`](/workflows/kinds/parent_id): Identifier of parent for step output
 * [`zone`](/workflows/kinds/zone): Definition of polygon zone
+* [`keypoint_detection_prediction`](/workflows/kinds/keypoint_detection_prediction): Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object
+* [`serialised_payloads`](/workflows/kinds/serialised_payloads): Serialised element that is usually accepted by sink
+* [`roboflow_api_key`](/workflows/kinds/roboflow_api_key): Roboflow API key
+* [`rgb_color`](/workflows/kinds/rgb_color): RGB color
+* [`image`](/workflows/kinds/image): Image in workflows
+* [`contours`](/workflows/kinds/contours): List of numpy arrays where each array represents contour points
+* [`roboflow_project`](/workflows/kinds/roboflow_project): Roboflow project name
+* [`language_model_output`](/workflows/kinds/language_model_output): LLM / VLM output
+* [`numpy_array`](/workflows/kinds/numpy_array): Numpy array
+* [`inference_id`](/workflows/kinds/inference_id): Inference identifier
+* [`dictionary`](/workflows/kinds/dictionary): Dictionary
+* [`detection`](/workflows/kinds/detection): Single element of detections-based prediction (like `object_detection_prediction`)
+* [`*`](/workflows/kinds/*): Equivalent of any element
+* [`top_class`](/workflows/kinds/top_class): String value representing top class predicted by classification model
+* [`qr_code_detection`](/workflows/kinds/qr_code_detection): Prediction with QR code detection
+* [`prediction_type`](/workflows/kinds/prediction_type): String value with type of prediction
 <!--- AUTOGENERATED_KINDS_LIST -->

inference/core/entities/common.py

@@ -3,7 +3,7 @@
 ModelID = Field(example="raccoon-detector-1", description="A unique model identifier")
 ModelType = Field(
     default=None,
-    example="object-detection",
+    examples=["object-detection"],
     description="The type of the model, usually referring to what task the model performs",
 )
 ApiKey = Field(

inference/core/env.py

@@ -458,6 +458,9 @@
 ALLOW_WORKFLOW_BLOCKS_ACCESSING_LOCAL_STORAGE = str2bool(
     os.getenv("ALLOW_WORKFLOW_BLOCKS_ACCESSING_LOCAL_STORAGE", "True")
 )
+ALLOW_WORKFLOW_BLOCKS_ACCESSING_ENVIRONMENTAL_VARIABLES = str2bool(
+    os.getenv("ALLOW_WORKFLOW_BLOCKS_ACCESSING_ENVIRONMENTAL_VARIABLES", "True")
+)
 WORKFLOW_BLOCKS_WRITE_DIRECTORY = os.getenv("WORKFLOW_BLOCKS_WRITE_DIRECTORY")
 
 DEDICATED_DEPLOYMENT_ID = os.getenv("DEDICATED_DEPLOYMENT_ID")

inference/core/version.py

@@ -1,4 +1,4 @@
-__version__ = "0.28.2"
+__version__ = "0.29.0"
 
 
 if __name__ == "__main__":

inference/core/workflows/core_steps/classical_cv/image_preprocessing/v1.py

@@ -90,7 +90,7 @@ class ImagePreprocessingManifest(WorkflowBlockManifest):
         description="Positive value to rotate clockwise, negative value to rotate counterclockwise",
         default=90,
         examples=[90, "$inputs.rotation_degrees"],
-        gte=-360,
+        ge=-360,
         le=360,
         json_schema_extra={
             "relevant_for": {

inference/core/workflows/core_steps/common/serializers.py

@@ -40,6 +40,8 @@
     WorkflowImageData,
 )
 
+MIN_SECRET_LENGTH_TO_REVEAL_PREFIX = 8
+
 
 def serialise_sv_detections(detections: sv.Detections) -> dict:
     serialized_detections = []
@@ -180,3 +182,12 @@ def serialize_dict(elements: Dict[str, Any]) -> Dict[str, Any]:
         value = serialize_wildcard_kind(value=value)
         serialized_result[key] = value
     return serialized_result
+
+
+def serialize_secret(secret: str) -> str:
+    if len(secret) < MIN_SECRET_LENGTH_TO_REVEAL_PREFIX:
+        return "*" * MIN_SECRET_LENGTH_TO_REVEAL_PREFIX
+    prefix = secret[:2]
+    infix = "*" * MIN_SECRET_LENGTH_TO_REVEAL_PREFIX
+    suffix = secret[-2:]
+    return f"{prefix}{infix}{suffix}"

inference/core/workflows/core_steps/flow_control/rate_limiter/v1.py

@@ -38,6 +38,14 @@
 
 * adjust `cooldown_seconds` to specify what is the number of seconds that must be awaited before next time
 when `step_2` is fired 
+
+
+!!! warning "Cooldown limitations"
+
+    Current implementation of cooldown is limited to video processing - using this block in context of a 
+    Workflow that is run behind HTTP service (Roboflow Hosted API, Dedicated Deployment or self-hosted 
+    `inference` server) will have no effect for processing HTTP requests.  
+    
 """
 
 

inference/core/workflows/core_steps/loader.py

@@ -91,6 +91,7 @@
 from inference.core.workflows.core_steps.common.serializers import (
     serialise_image,
     serialise_sv_detections,
+    serialize_secret,
     serialize_video_metadata_kind,
     serialize_wildcard_kind,
 )
@@ -217,6 +218,9 @@
 from inference.core.workflows.core_steps.models.third_party.qr_code_detection.v1 import (
     QRCodeDetectorBlockV1,
 )
+from inference.core.workflows.core_steps.secrets_providers.environment_secrets_store.v1 import (
+    EnvironmentSecretsStoreBlockV1,
+)
 from inference.core.workflows.core_steps.sinks.email_notification.v1 import (
     EmailNotificationBlockV1,
 )
@@ -233,6 +237,12 @@
 from inference.core.workflows.core_steps.sinks.roboflow.model_monitoring_inference_aggregator.v1 import (
     ModelMonitoringInferenceAggregatorBlockV1,
 )
+from inference.core.workflows.core_steps.sinks.slack.notification.v1 import (
+    SlackNotificationBlockV1,
+)
+from inference.core.workflows.core_steps.sinks.twilio.sms.v1 import (
+    TwilioSMSNotificationBlockV1,
+)
 from inference.core.workflows.core_steps.sinks.webhook.v1 import WebhookSinkBlockV1
 from inference.core.workflows.core_steps.transformations.absolute_static_crop.v1 import (
     AbsoluteStaticCropBlockV1,
@@ -379,6 +389,7 @@
     ROBOFLOW_API_KEY_KIND,
     ROBOFLOW_MODEL_ID_KIND,
     ROBOFLOW_PROJECT_KIND,
+    SECRET_KIND,
     SERIALISED_PAYLOADS_KIND,
     STRING_KIND,
     TOP_CLASS_KIND,
@@ -397,6 +408,7 @@
     "thread_pool_executor": None,
     "allow_access_to_file_system": ALLOW_WORKFLOW_BLOCKS_ACCESSING_LOCAL_STORAGE,
     "allowed_write_directory": WORKFLOW_BLOCKS_WRITE_DIRECTORY,
+    "allow_access_to_environmental_variables": ALLOW_WORKFLOW_BLOCKS_ACCESSING_LOCAL_STORAGE,
 }
 
 KINDS_SERIALIZERS = {
@@ -407,6 +419,7 @@
     KEYPOINT_DETECTION_PREDICTION_KIND.name: serialise_sv_detections,
     QR_CODE_DETECTION_KIND.name: serialise_sv_detections,
     BAR_CODE_DETECTION_KIND.name: serialise_sv_detections,
+    SECRET_KIND.name: serialize_secret,
     WILDCARD_KIND.name: serialize_wildcard_kind,
 }
 KINDS_DESERIALIZERS = {
@@ -552,6 +565,9 @@ def load_blocks() -> List[Type[WorkflowBlock]]:
         RoboflowObjectDetectionModelBlockV2,
         VLMAsClassifierBlockV2,
         VLMAsDetectorBlockV2,
+        EnvironmentSecretsStoreBlockV1,
+        SlackNotificationBlockV1,
+        TwilioSMSNotificationBlockV1,
     ]
 
 
@@ -591,4 +607,5 @@ def load_kinds() -> List[Kind]:
         IMAGE_METADATA_KIND,
         BYTES_KIND,
         INFERENCE_ID_KIND,
+        SECRET_KIND,
     ]

inference/core/workflows/core_steps/models/foundation/anthropic_claude/v1.py

@@ -25,6 +25,7 @@
     INTEGER_KIND,
     LANGUAGE_MODEL_OUTPUT_KIND,
     LIST_OF_VALUES_KIND,
+    SECRET_KIND,
     STRING_KIND,
     ImageInputField,
     Selector,
@@ -149,7 +150,7 @@ class BlockManifest(WorkflowBlockManifest):
             },
         },
     )
-    api_key: Union[Selector(kind=[STRING_KIND]), str] = Field(
+    api_key: Union[Selector(kind=[STRING_KIND, SECRET_KIND]), str] = Field(
         description="Your Antropic API key",
         examples=["xxx-xxx", "$inputs.antropics_api_key"],
         private=True,
@@ -220,7 +221,7 @@ def describe_outputs(cls) -> List[OutputDefinition]:
 
     @classmethod
     def get_execution_engine_compatibility(cls) -> Optional[str]:
-        return ">=1.3.0,<2.0.0"
+        return ">=1.4.0,<2.0.0"
 
 
 class AntropicClaudeBlockV1(WorkflowBlock):

inference/core/workflows/core_steps/models/foundation/google_gemini/v1.py

@@ -23,6 +23,7 @@
     IMAGE_KIND,
     LANGUAGE_MODEL_OUTPUT_KIND,
     LIST_OF_VALUES_KIND,
+    SECRET_KIND,
     STRING_KIND,
     ImageInputField,
     Selector,
@@ -158,7 +159,7 @@ class BlockManifest(WorkflowBlockManifest):
             },
         },
     )
-    api_key: Union[Selector(kind=[STRING_KIND]), str] = Field(
+    api_key: Union[Selector(kind=[STRING_KIND, SECRET_KIND]), str] = Field(
         description="Your Google AI API key",
         examples=["xxx-xxx", "$inputs.google_api_key"],
         private=True,
@@ -223,7 +224,7 @@ def describe_outputs(cls) -> List[OutputDefinition]:
 
     @classmethod
     def get_execution_engine_compatibility(cls) -> Optional[str]:
-        return ">=1.3.0,<2.0.0"
+        return ">=1.4.0,<2.0.0"
 
 
 class GoogleGeminiBlockV1(WorkflowBlock):

inference/core/workflows/core_steps/models/foundation/google_vision_ocr/v1.py

@@ -22,6 +22,7 @@
 from inference.core.workflows.execution_engine.entities.types import (
     IMAGE_KIND,
     OBJECT_DETECTION_PREDICTION_KIND,
+    SECRET_KIND,
     STRING_KIND,
     Selector,
 )
@@ -79,7 +80,7 @@ class BlockManifest(WorkflowBlockManifest):
             },
         },
     )
-    api_key: Union[Selector(kind=[STRING_KIND]), str] = Field(
+    api_key: Union[Selector(kind=[STRING_KIND, SECRET_KIND]), str] = Field(
         description="Your Google Vision API key",
         examples=["xxx-xxx", "$inputs.google_api_key"],
         private=True,
@@ -97,7 +98,7 @@ def describe_outputs(cls) -> List[OutputDefinition]:
 
     @classmethod
     def get_execution_engine_compatibility(cls) -> Optional[str]:
-        return ">=1.3.0,<2.0.0"
+        return ">=1.4.0,<2.0.0"
 
 
 class GoogleVisionOCRBlockV1(WorkflowBlock):